Control costs. Reduce risk.
Master procurement.

Model Layer

• •OpenAI, Anthropic, Google DeepMind, Meta — evaluate fit, pricing, and lock-in risk
• •Define fine-tuning vs. RAG vs. prompt engineering strategy
• •Negotiate API pricing tiers and enterprise agreements

Model selection is an architectural decision, not a vendor preference.

Compute & Cost Layer

• •NVIDIA, AMD, AWS, Azure — GPU procurement and cloud AI spend
• •Right-size inference vs. training infrastructure
• •Implement cost guardrails and usage monitoring

Compute costs compound fast without governance.

Data & Orchestration Layer

• •Databricks, Snowflake, Palantir, H2O.ai — governed data pipelines for AI
• •Establish vector database and retrieval architecture
• •Ensure data quality, lineage, and access controls

Governance & Risk Layer

• •ServiceNow, IBM, OneTrust, DataRobot — AI policy and compliance
• •Define model risk management and audit trails
• •Align with emerging AI regulatory frameworks

Procurement Strategy

• •Avoid vendor lock-in with modular architecture
• •Structure pilots with clear success criteria and exit clauses
• •Tie spend to measurable business outcomes

AIRONCLAD has guided $200M+ in AI infrastructure decisions.

Discover & Normalize

• •Consolidate app inventory across departments
• •Map owners, contracts, renewal dates, and criticality
• •Normalize spend by vendor, product, and cost center

You can't optimize what you can't see.

Utilization & License Recovery

• •Identify inactive and underused seats
• •Reharvest licenses before renewals
• •Align entitlements to role-based access

Savings come from usage, not wishful budgeting.

Consolidate & Standardize

• •Identify overlapping capabilities (3 tools doing 1 job)
• •Select anchor platforms per category
• •Create exception process with time-bound approvals

Contract & Renewal Control

• •Build renewal calendar and negotiation cadence
• •Eliminate auto-renew surprises
• •Use benchmarks and competitive pressure

Operating Model

• •Define intake and standards for new SaaS requests
• •Establish quarterly stack review
• •Tie to security and finance governance

This becomes a repeatable system, not a one-time audit.

Inventory & Line Hygiene

• •Identify all lines, devices, circuits, and plans
• •Remove unused lines and stale circuits
• •Validate users, locations, and business purpose

Rate Plan & Usage Alignment

• •Right-size plans based on actual utilization
• •Reduce overages and premium add-ons
• •Standardize device and plan catalogs

Carrier Strategy & Negotiation

• •Benchmark rates and terms
• •Consolidate carriers where it improves leverage
• •Rebid with service-level commitments

Network Modernization

• •Evaluate SD-WAN and broadband substitution
• •Reduce MPLS dependency where feasible
• •Improve resilience with dual-path design

Governance & Chargeback

• •Monthly exceptions review
• •Automated disconnect workflows
• •Transparent showback and chargeback reporting

Control Coverage Map

• •Map tools to NIST/CSF capabilities
• •Identify gaps and overlaps
• •Align tools to threat model and risk priorities

Platform Consolidation

• •Reduce point-solution sprawl
• •Standardize on core security platforms (identity, endpoint, SIEM)
• •Ensure interoperability and data quality

Detection & Response Operations

• •Improve alert fidelity (less noise)
• •Define incident playbooks and escalation
• •Measure MTTD/MTTR and tune continuously

Governance, Risk & Compliance

• •Centralize policies, controls, and evidence
• •Implement risk-based prioritization
• •Automate compliance reporting where possible

Security Economics

• •Tie spend to measurable risk reduction
• •Rationalize renewals based on outcomes
• •Use architecture standards to prevent tool creep

Visibility & Allocation

• •Standardize tagging and ownership
• •Allocate cost by product, team, and environment
• •Establish accurate showback and chargeback

Waste Elimination

• •Rightsize compute and storage
• •Remove idle resources
• •Optimize data transfer and backups

Commitment Strategy

• •Use reserved instances and savings plans responsibly
• •Align commitments to stable workloads
• •Avoid over-committing to forecast fiction

Guardrails & Policy

• •Budget alerts and anomaly detection
• •Provisioning standards and approval paths
• •Environment lifecycle management

KPI Dashboard

• •Unit cost metrics (cost per transaction, order, etc.)
• •Optimization pipeline and realized savings
• •Forecast accuracy and variance tracking

Core Landscape Baseline

• •Current-state architecture and pain points
• •Lifecycle status, supportability, and cost
• •Critical business processes and dependencies

Modernization Pathways

• •Upgrade vs. replatform vs. replace decisioning
• •Decouple with APIs and event integration
• •Reduce monolith dependency over time

Integration & Data Foundation

• •Standardize integration patterns (API, iPaaS, events)
• •Establish governed master and reference data
• •Improve data quality for analytics and AI readiness

Identity & Access

• •Consolidate IAM and enforce least privilege
• •Strengthen SSO, MFA, and privileged access
• •Align identity to Zero Trust principles

Delivery & Risk Management

• •Phased rollout with rollback plans
• •Cutover rehearsals and business readiness
• •Measure stability, cycle time, and run cost